Department of Computer Science and Engineering, Center for Cognitive Science, The Ohio State University, Columbus, OH, 43210, USA,
Cogn Neurodyn. 2008 Mar;2(1):7-19. doi: 10.1007/s11571-007-9035-8. Epub 2008 Jan 10.
We present a neurocomputational model for auditory streaming, which is a prominent phenomenon of auditory scene analysis. The proposed model represents auditory scene analysis by oscillatory correlation, where a perceptual stream corresponds to a synchronized assembly of neural oscillators and different streams correspond to desynchronized oscillator assemblies. The underlying neural architecture is a two-dimensional network of relaxation oscillators with lateral excitation and global inhibition, where one dimension represents time and another dimension frequency. By employing dynamic connections along the frequency dimension and a random element in global inhibition, the proposed model produces a temporal coherence boundary and a fissure boundary that closely match those from the psychophysical data of auditory streaming. Several issues are discussed, including how to represent physical time and how to relate shifting synchronization to auditory attention.
我们提出了一个用于听觉流的神经计算模型，这是听觉场景分析中的一个突出现象。所提出的模型通过振荡相关来表示听觉场景分析，其中感知流对应于神经振荡器的同步集合，而不同的流对应于去同步振荡器集合。基础的神经结构是一个具有侧向激励和全局抑制的二维松弛振荡器网络，其中一个维度表示时间，另一个维度表示频率。通过在频率维度上采用动态连接和全局抑制中的随机元素，所提出的模型产生了一个与听觉流的心理物理数据非常匹配的时间相干边界和裂缝边界。讨论了几个问题，包括如何表示物理时间以及如何将同步转移与听觉注意力联系起来。
